Work Sampling Data Research Articles

Advancements in Data Analysis for the Work-Sampling Method

The work-sampling method makes it possible to gain valuable insights into what is happening in production systems. Work sampling is a process used to estimate the proportion of shift time that workers (or machines) spend on different activities (within productive work or losses). It is estimated based on enough random observations of activities over a selected period. When workplace operations do not have short cycle times or high repetition rates, the use of such a statistical technique is necessary because the labor sampling data can provide information that can be used to set standards. The work-sampling procedure is well standardized, but additional contributions are possible when evaluating the observations. In this paper, we present our contribution to improving the decision-making process based on work-sampling data. We introduce a correlation comparison of the measured hourly shares of all activities in pairs to check whether there are mutual connections or to uncover hidden connections between activities. The results allow for easier decision-making (conclusions) regarding the influence of the selected activities on the triggering of the others. With the additional calculation method, we can uncover behavioral patterns that would have been overlooked with the basic method. This leads to improved efficiency and productivity of the production system.

ANALYSIS OF NOISE MEASUREMENTS IN THE WORK AREA TO THE OPERATOR'S HEARING IN THE PROCESS DEPARTMENT USING THE WORK SEMPLING METHOD

PT. Ika Bina Agro Wisesa (IBAS) is one of the palm oil mills on the island of Sumatra, Indonesia. This palm oil factory is located in the village of Guha Uleue, Kuta makmur District, North Aceh District, Aceh province. The problem in this study is to identify and deal with the problems encountered by applying theory and concepts with work and idle calculations carried out using work sampling data on 3 operators in the Drying department. The research was carried out with the work and idle calculation time being carried out for 1 week. All Operators working on the production floor work from 08.00 to 16.00 with breaks from 12.00 to 13.00. The number of minutes from 08.00-12.00 and 13.00-16.00 means the total population in this study is 84. The purpose of this study is to analyze the measurement of noise in employees as seen from the effect of noise. The effect of noise will later be used to determine what is the influence of noise by each employee to complete his work in the process department. As for the results of this study there is an analysis of noise measurements using a Sound Level Meter (SLM) which has a noise level between 81.3 dB(A) to 88.9 dB(A). then PT. Ika Bina Agro Wisesa has a hearing protection program contained in the HSE Code of Practice-00612. The results of the study of measuring noise intensity 8 working hours for the operator position on Personal Noise Level dB (A) boiler 84.4, Personal Noise Level dB (A) polishing drum is 81.3, Personal Noise Level dB (A) ripple mill 88.9 and finally Personal Noise Level dB (a) The sterilizer is 67.7. this is in line with the Decree of the Minister of Manpower and Transmigration No. 13 of 2011 and the Decree of the Minister of Energy and Mineral Resources of the Republic of Indonesia No. 1827 of 2018 which is used to analyze and control noise in the processing plant area.
 

STUDI KASUS ANALISIS BEBAN KERJA BERDASARKAN WAKTU KERJA KARYAWAN PADA UNIT PEMANENAN AFDELING 1 DI KEBUN KELAPA SAWIT PT. XYZ

The importance of quality human resources in oil palm plantations in the field of harvesting to achieve high productivity, the success of harvesters is also very much determined by the pressure of the workload that is owned by workers, the workload depends on the job description compiled by the company. also the possibility of a workload that is too high. This study aims to analyze the working time of harvest employees and determine the productive, unproductive and personal time of harvest employees and analyze the number of harvest employees needed at PT. XYZ. This research was conducted at PT. XYZ Tanjung Batu Village, Derawan Island District, Berau Regency, East Kalimantan. This research was conducted using work sampling data collection method, namely observing the working time of harvest employees with 10 minutes intervals for 7 working hours by noting productive time, unproductive time and personal time. The results from the observations of researchers through the characteristics of harvest workers that affect the characteristics of age and height characteristics, it is proven that the age of 20 - 29 years is faster to reach the target or basis compared to the age of 30 - 49 years. And the characteristics of height have an effect on reaching the target, it is proven that height 170 - 179 cm reaches the target or base faster than 150 - 159 cm. And the observations of researchers from 16 respondents harvest productive working time an average of 73.52%, 17.20% unproductive time and 9.28% personal time. Calculation of the need for harvest workers in 1 division (763.33 ha) results in 33,644 rounded up to 34 harvest workers, the results needed in 1 division (763.33 ha) through the calculation of the time of completion of tasks (WPT).

The dynamics of design: exploring heterogeneity in meso-scale team processes

There is a critical gap in understanding how meso-scale team processes - interactions between individuals in a team - develop in design teams and specifically how they dynamically balance design with managerial effort. We treat this deficit by contrasting two in-depth cases using work sampling data. We identify a number of contributions. First, we describe how design team processes display both goal/action and temporal heterogeneity. Second, we demonstrate how this heterogeneity is underpinned by common principles that consistently shape team processes in design. Specifically: proportional goal/action composition and recurring process patterns over time. Finally, we describe how these principles can be integrated via ‘archetypal process types’. Together, these substantially extend prior theory and point to specific implications for future design research.

Balancing traditional activities and cognitive pharmaceutical services by community pharmacists: a work sampling study

Background Community pharmacy is undergoing a transition, shifting focus from traditional roles to the provision of cognitive pharmaceutical services. However, traditional activities performed by community pharmacists reduce the amount of available time for implementing and providing such services. Therefore, hampering the community pharmacist in the transition. Objective The aim of this study was to identify characteristics of community pharmacists that spend a higher proportion of their time on cognitive pharmacy services and to identify activities that compete with time spent on such activities by community pharmacists. Setting Daily community pharmacy practice. Method Self-reporting work sampling using smartphone technology was used to register the activities of community pharmacists. Participating pharmacists recorded their current activity five times per working day for 6 weeks and also completed an online survey about baseline characteristics. Main outcome measure Time utilization. Results Ninety-one Dutch community pharmacists provided work-sampling data. The results showed that Dutch community pharmacists are predominantly spending less time on managerial activities when spending more time on cognitive services (from 25.7% to 14.5%, p = 0.016). Pharmacists who are spending more time on such services, want to spend even more time on direct patient contact compared to pharmacists who spend less time on it (p = 0.030). Conclusion This study shows that community pharmacists that spend more time on cognitive pharmacy services are devoting less time on managerial activities, logistics and other activities. Pharmacists spending more time on cognitive pharmaceutical services are mostly locum pharmacists or work at a pharmacy located in a residential area with largely older inhabitants.

Pharmacy in transition: A work sampling study of community pharmacists using smartphone technology.

The nature of community pharmacy is changing, shifting from the preparation and distribution of medicines to the provision of cognitive pharmaceutical services (CPS); however, often the provision of traditional services leaves little time for innovative services. This study investigated the time community pharmacists spend on the tasks and activities of daily practice and to what extent they are able to implement CPS-related services in daily practice. Self-reporting work sampling was used to register the activities of community pharmacists. A smartphone application, designed specifically for this purpose, alerted participants to register their current activity five times per working day for 6 weeks. Participants also completed an online survey about baseline characteristics. Ninety-one Dutch community pharmacists provided work-sampling data (7848 registered activities). Overall, 51.5% of their time was spent on professional activities, 35.4% on semi-professional activities, and 13.1% on non-professional activities. The proportion of time devoted to CPS decreased during the workweek, whereas the time spent on traditional task increased. This study shows it is feasible to collect work-sampling data using smartphone technology. Community pharmacists spent almost half of their time on semi-professional and non-professional activities, activities that could be delegated to other staff members. In practice, the transition to CPS is hampered by competing traditional tasks, which prevents community pharmacists from profiling themselves as pharmaceutical experts in daily practice.

How Do Nurses Spend Their Time in The Hospital?

Purpose: The current study investigated the productivity of nurses in emergency department, ICU and CCU of Shahid-Madani hospital in Tabriz. Methods: A two-stage time and motion study was conducted; the observational work sampling study was undertaken by 15 nurses, followed by self-reporting work sampling study by 42 nurses over a period of five weeks. Descriptive and analytical statistics were used to analyze the data. Results: Fifty-seven work sampling data were collected, 15 through the observational study and 42 in self-reporting. Considerable differences were found in the nurses’ time distribution between two techniques. Percentage of direct, indirect and personal activities in observational versus self-reporting were observed (32.74% versus 40.52%), (24.09% versus 28.84%) and (42.30% versus 30.41%) respectively. Conclusion: A considerable proportion of nurses’ time in each shift was spent on their personal activities, which would affect their productivity as well as their direct and indirect delivered cares for patients. Identifying the percentage of spent time on nurses’ personal activities would be a useful measure for improving patient care protocols in the hospitals.

Using the Pda as an Educational Tool to Collect Work Measurement Data

As human factors (HF) educators, we often struggle to find good, inexpensive tools that allow us to demonstrate both basic principles and practical applications. The following computer software, available on Palm Zires, allows students to collect work sampling data (with QuikSamp) and conduct time studies (with QuikTS) on the least expensive PDAs available, so that multiple units can be purchased at relatively low cost. In addition to the data collection capabilities, the students can also examine the tradeoffs between sample size and the accuracy of the study and other basic work measurement principles.

A work-sampling tool to measure the effect of electronic medical record implementation on health care workers.

This article presents baseline work sampling data from an outpatient oncology clinic prior to an electronic medical record implementation. The physicians and medical office assistants spent 29% and 39% of their time, respectively, entering and retrieving information from medical records. The physicians and medical office assistants spent 43% and 17% of their time, respectively, on direct patient contact. Using scheduled outpatient counts to measure the productivity of the physicians and medical office assistants failed to capture 19% and 29% of their workload.

Work Sampling Can Predict Unit Rate Productivity

Various methods are employed to measure labor utilization during power plant construction, one of which is work sampling. Work sampling attempts to evaluate how the work force spends its time at work. This provides timely information to management in order to determine whether corrective action or detailed study is needed to achieve a higher degree of efficiency. However, the effectiveness of work sampling in demonstrating true labor performance has not been statistically verified using data collected at construction sites. This study collects 45 work sampling data points from 11 nuclear power projects and 4 fossil fuel power projects. the relationship between work sampling and productivity has been strongly supported by this statistical analysis. This study also verifies that work sampling is a good labor productivity indicator as well as a useful predictor in a productivity projection model.

Improving Productivity Estimates by Work Sampling

Theoretical aspects are presented to evaluate the adequacy of work sampling as a surrogate productivity measure. A 10‐week study is described in which work sampling data were gathered simultaneously with earned value information for a 10‐man, small‐bore pipefitter crew. Two forms of work sampling data were gathered that differed principally in the definition of direct work. The direct work percentages are statistically correlated to the ratio of earned to actual man‐hours, and it is shown that the Pearson product‐moment correlation coefficient could be improved by as much as 86% if the definition of direct work is restricted. The probability of a Type I statistical error is also greatly reduced. Data summarized according to 5‐ or 7‐day moving averages is found to be more reliable than daily or weekly averages. It is shown how a prediction equation could be developed. The slope of this equation suggests that rather significant changes in the earned to actual man‐hour ratio are reflected by rather small cha...

Selection of Work Sampling Observation Times: Part I—Stratified Sampling

Abstract Various methods of selecting observation times in work sampling studies are presented, including simple random, systematic, and stratified sampling, and a new method called restricted random sampling. The attributes of these sampling methods are evaluated, particularly statistical efficiency, and the important advantages of stratification are demonstrated. Finally, the analysis of variance is recommended for statistical analysis of work sampling data to account for the presence of several sources of variation, in addition to sampling error.